# Load Libraries
library(vegan)

# Load data
Brier_Ck<-read.csv("Brier_Ck.csv", header= T, row.names = 1)

#Dimensions of the matrix (dim function)
dim(Brier_Ck)

#List variables in the data (names function)
names(Brier_Ck)

#Get the 5 most abundant species
abundance<-apply(Brier_Ck,MARGIN=2,sum)

#sorting and print the top 5 species
sort(abundance, decreasing = T)[1:5]

# Make a presence/absence matrix
Brier_Ck_pa<-decostand(Brier_Ck, method="pa")

# This works also
Brier_Ck_pa2<-Brier_Ck[]
Brier_Ck_pa2[Brier_Ck>0]<-1

# Get number of species by site
site_s<-apply(Brier_Ck_pa,1,sum)
site_s

# eliminate sites with 2 or fewer species
#save result at Brier_Ck_2
Brier_Ck_2<-Brier_Ck[site_s>2,]

#eliminate species with a total abundance less than 10 
#use apply to get species abundance
species_abund<-apply(Brier_Ck_2,2,sum)

#eliminate columns (species) with low abundance
#save resul as Brier_Ck_3
Brier_Ck_3<-Brier_Ck_2[,species_abund>10]

# get dimensions of final matrix
dim(Brier_Ck_3)

# log transform
Brier_Ck_3_log<-log(Brier_Ck_3+1)

#write to file
write.csv(Brier_Ck_3_log,"final_matrix.csv")